A data-characteristic-aware latent factor model for web services QoS prediction D Wu, X Luo, M Shang, Y He, G Wang, X Wu IEEE Transactions on Knowledge and Data Engineering 34 (6), 2525-2538, 2020 | 193 | 2020 |
A deep latent factor model for high-dimensional and sparse matrices in recommender systems D Wu, X Luo, M Shang, Y He, G Wang, MC Zhou IEEE Transactions on Systems, Man, and Cybernetics: Systems 51 (7), 4285-4296, 2019 | 187 | 2019 |
Refractive index sensing based on Mach–Zehnder interferometer formed by three cascaded single-mode fiber tapers D Wu, T Zhu, M Deng, DW Duan, LL Shi, J Yao, YJ Rao Applied optics 50 (11), 1548-1553, 2011 | 175 | 2011 |
In-line fiber optic interferometric sensors in single-mode fibers T Zhu, D Wu, M Liu, DW Duan Sensors 12 (8), 10430-10449, 2012 | 170 | 2012 |
Algorithms of unconstrained non-negative latent factor analysis for recommender systems X Luo, M Zhou, S Li, D Wu, Z Liu, M Shang IEEE Transactions on Big Data 7 (1), 227-240, 2019 | 150 | 2019 |
A latent factor analysis-based approach to online sparse streaming feature selection D Wu, Y He, X Luo, MC Zhou IEEE Transactions on Systems, Man, and Cybernetics: Systems 52 (11), 6744-6758, 2021 | 143 | 2021 |
All single-mode fiber Mach–Zehnder interferometer based on two peanut-shape structures D Wu, T Zhu, KS Chiang, M Deng Journal of Lightwave Technology 30 (5), 805-810, 2012 | 143 | 2012 |
An L1-and-L2-Norm-Oriented Latent Factor Model for Recommender Systems D Wu, M Shang, X Luo, Z Wang IEEE Transactions on Neural Networks and Learning Systems 33 (10), 5775-5788, 2021 | 139 | 2021 |
Prediction of the spatial distribution of Alternanthera philoxeroides in China based on ArcGIS and MaxEnt H Yan, L Feng, Y Zhao, L Feng, D Wu, C Zhu Global Ecology and Conservation 21, e00856, 2020 | 131 | 2020 |
A posterior-neighborhood-regularized latent factor model for highly accurate web service QoS prediction D Wu, Q He, X Luo, M Shang, Y He, G Wang IEEE Transactions on Services Computing 15 (2), 793-805, 2019 | 122 | 2019 |
Self-training semi-supervised classification based on density peaks of data D Wu, M Shang, X Luo, J Xu, H Yan, W Deng, G Wang Neurocomputing 275, 180-191, 2018 | 117 | 2018 |
Robust latent factor analysis for precise representation of high-dimensional and sparse data D Wu, X Luo IEEE/CAA Journal of Automatica Sinica 8 (4), 796-805, 2020 | 108 | 2020 |
In-fiber Mach–Zehnder interferometer formed by large lateral offset fusion splicing for gases refractive index measurement with high sensitivity DW Duan, YJ Rao, LC Xu, T Zhu, D Wu, J Yao Sensors and Actuators B: chemical 160 (1), 1198-1202, 2011 | 108 | 2011 |
A Highly Accurate Framework for Self-Labeled Semisupervised Classification in Industrial Applications D Wu, X Luo, G Wang, M Shang, Y Yuan, H Yan IEEE Transactions on Industrial Informatics 14 (3), 909-920, 2018 | 100 | 2018 |
A double-space and double-norm ensembled latent factor model for highly accurate web service QoS prediction D Wu, P Zhang, Y He, X Luo IEEE Transactions on Services Computing 16 (2), 802-814, 2022 | 67 | 2022 |
A prediction-sampling-based multilayer-structured latent factor model for accurate representation to high-dimensional and sparse data D Wu, X Luo, Y He, M Zhou IEEE Transactions on Neural Networks and Learning Systems 35 (3), 3845-3858, 2022 | 66 | 2022 |
A high temperature sensor based on a peanut-shape structure Michelson interferometer D Wu, T Zhu, M Liu Optics Communications 285 (24), 5085-5088, 2012 | 66 | 2012 |
Water eutrophication evaluation based on rough set and petri nets: A case study in Xiangxi-River, Three Gorges Reservoir H Yan, Y Huang, G Wang, X Zhang, M Shang, L Feng, J Dong, K Shan, ... Ecological Indicators 69, 463-472, 2016 | 56 | 2016 |
In-line all-fibre Fabry-Perot interferometer high temperature sensor formed by large lateral offset splicing DW Duan, YJ Rao, WP Wen, J Yao, D Wu, LC Xu, T Zhu Electronics letters 47 (6), 401-403, 2011 | 46 | 2011 |
Toward mining capricious data streams: A generative approach Y He, B Wu, D Wu, E Beyazit, S Chen, X Wu IEEE transactions on neural networks and learning systems 32 (3), 1228-1240, 2020 | 43 | 2020 |